Efficient HEVC-to-VVC Transcoder Based On A Bayesian Classifier For The First Quadtree Depth Level

Autor: Antonio Jesús Díaz-Honrubia, Pedro Cuenca, Thanuja Mallikarachchi, David García-Lucas, Gabriel Cebrián-Márquez
Rok vydání: 2020
Předmět:
Zdroj: ICIP
DOI: 10.1109/icip40778.2020.9190640
Popis: In the coming years, the Versatile Video Coding (VVC) standard will be launched to replace the current High Efficiency Video Coding (HEVC) standard, making it necessary to find efficient methods to convert existing multimedia content to the new format. However, transcoding is a complex pipeline composed of a decoding and an encoding process that involves long processing times. On the basis of the existing correlation between the block partitioning structures of both standards, this paper presents an HEVC-to-VVC transcoding scheme. The proposed method consists of a Naive-Bayes classifier that assists the partitioning decision at the first level of quadtree by using features extracted from the $128\times 128$ pixel blocks of the residual and reconstructed frames in HEVC. The experimental results using random access configuration show an average transcoding time reduction of 13.38% at the cost of a compression efficiency loss of 0.32% in terms of BD-rate.
Databáze: OpenAIRE